November 30, 2022
How Corporate C-Levels Can Serve as the Guardians of Ethical Artificial Intelligence

How Corporate C-Levels Can Serve as the Guardians of Ethical Artificial Intelligence

There is no doubt that we are now living in the age of artificial intelligence, what with all the attention given to it and the possibilities it supposedly holds. There are others who claim that we haven’t even scratched the surface of what’s possible with AI, but I disagree and think we’ve progressed far enough to envision its broad usage already.

The ethical use of AI has emerged as a contentious issue due to its pervasiveness in modern business operations. Is there evidence that businesses throughout the world are employing AI in a moral and ethical manner?

The standard for AI’s future usage and consideration will be defined by its ethical application. Due to the increasing importance of AI, it is imperative that businesses adopt the most ethical AI practices possible. Reputational harm and legal entanglements can emerge from irresponsible AI use. In this way, using AI in an ethical manner safeguards not just your good name but also your legal status.

Nearly three-quarters of the world’s largest companies, according to Gartner, will employ AI specialists by 2023 to oversee brand and reputation risk. By doing so, they may be assured that their AI practices will never violate any applicable laws.

To what extent a corporation puts its artificial intelligence initiative to use will depend heavily on the CTO and CEO. In order to gauge whether or not their AI practices are ethical, CEOs might ask themselves whether or not they would be embarrassed if their company’s AI use was made public.

What Motivates and Causes Unrestrained AI Use

Artificial intelligence has a long history of flops. There are several instances where AI algorithms have let people down and failed to provide the expected outcomes.

Amazon recently learned that its AI recruiting algorithm automatically disqualified any and all female applicants. Points out of five were given to each contender, much to Amazon’s star rating system. Only the highest-rated applicants were evaluated for open positions inside the organization. However, insiders learned that the system actively discriminated against women.

The use of artificial intelligence by traffic police in key Chinese cities to monitor jaywalkers in 2018 was a disastrous misstep. As part of their tracking operation, the cops made a fool of themselves when they mistook the visage of Chinese millionaire Dong Mingzhu for a jaywalker. Dong’s face was found on a bus that had been plastered with posters for an advertising campaign. The city’s traffic cops were the target of internet ridicule after the gaffe.

Biases associated to artificial intelligence can be seen in a variety of contexts, including credit scoring, erroneous medical diagnosis, recruiting, and judicial sentence. As a result of AI biases, businesses may be unable to effectively carry out essential activities, which may have serious future legal ramifications.

Managers at the highest levels of an organization need to take note of this blunder and make changes to their procedures to reduce AI bias. They need to take all necessary precautions in the future with their AI procedures to ensure they don’t end up in the same situation. AI and the technology it entails should be utilized for good, not to further bigotry or discrimination of any kind.

Most of the time, flawed AI is the product of sloppy data or HR practices. Neglecting to hire a diverse pool of candidates while building your AI team might have negative consequences down the line. Furthermore, the adoption of AI might be hindered by mistakes made during data collecting or training.

Repercussions of Abuse of Artificial Intelligence

The risks associated with the improper application of AI are substantial. To begin, it’s important to note that customer data is at risk whenever AI is used inappropriately. A company or organization’s image might take a serious hit if they make a mistake when managing sensitive client information.

These are some further examples of unfortunate events:

Loss of Trust 

A company’s good name is second only to its cash on hand in terms of importance to its success. Goodwill is an asset that many companies use to market and sell their products. This credibility, however, might be damaged by a botch job. The vast majority of consumers are up-to-date on the newest industry trends, and they will quickly turn their backs on businesses who are exposed as being complicit in AI frauds.

Negative Impact on Revenue Streams 

What happens if your credibility and standing in the community plummet? Your revenue streams are drying up. As a result of the company’s lack of care for their AI systems, consumers may choose to shop elsewhere. Customers are aware of the worth of their data and are less likely to fall for data scams in light of the current surge of attacks on social media platforms and within companies. Therefore, if your AI system has any sort of bias or anomaly, your consumers will detect it right away and, if required, take preventative measures.

Legal Implications 

Misuse of AI, as was briefly discussed above, can potentially have serious legal consequences. To comply with laws like the General Data Protection Regulation, organizations must be very careful when using AI systems. They might be in legal trouble if client information is lost or misused. Your legal or compliance framework should be up-to-date on the rules governing AI and data, and should help you follow them.

Setting Up an Ethical Framework

Stakeholders and managers, as well as the rest of the C-suite, should contribute to the creation of an ethical framework. Integrating ethics into your AI approach is essential. Strategies for ethical AI should emphasize team diversity, a competent staff, and openness to sharing data. The use of AI at your company should be something you can brag about with ease.

The second step is to do thorough pre-implementation testing of all training models to root out any biases. If you want to keep biases and inconsistencies to a minimum in your training models, you should validate and control them before rolling them out to the whole company.

Proper data collection and storage, which can be ensured with the help of good AI governance, may set the tone for any AI campaign. There won’t be any better information to work with than yours.

In conclusion, compliance should be a top concern for risk management. The increasing legal danger has to be addressed as efficiently as feasible, especially in light of recent regulatory developments in this area. Responsibility for the compliance process should be shared across the whole business, not only with IT. Get permission from customers to collect their information before doing so. Integrate AI responsibly into your business practices to strengthen the relationship between the two.


Organizational leaders are responsible for ensuring that AI is used ethically and in a responsible manner. Chief executives (CEOs) should serve as guardians of ethical AI use and establish a culture of ethical AI adoption throughout the company.

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